PAKLOCCORPUS AS A DATA-DRIVEN LEARNING TOOL IN ESL CLASSROOMS

Abstract

PakLocCorpus represents a locally grounded linguistic resource reflecting authentic usage of English in Pakistan across academic, media, and literary registers. Through classroom experiments involving corpus searches, collocation analysis, and context-based vocabulary learning, students engaged with data reflecting their own sociolinguistic reality. This study explores the use of PakLocCorpus, a purpose-built corpus of Pakistani English, as a Data-Driven Learning (DDL) tool in English as a Second Language (ESL) classrooms. Drawing inspiration from the Corpus of Contemporary American English (COCA) classroom study by Lopes (2013), social language tool from Gee (2011) and guidelines from Smith and Robbins (2023), this research investigates how Pakistani ESL learners can use corpus consultation to improve vocabulary, grammar, and cultural awareness. Results reveal significant gains in lexical competence, accuracy in collocation use, grammatical understanding, and positive attitudes toward Pakistani English. Findings show that Urduized words have a high acceptance rate in ESL students. The study argues that data-driven learning with PakLocCorpus bridges the gap between global linguistic competence and local identity. It empowers learners as researchers of their own language, fosters autonomy, and integrates local culture in the ESL curriculum. The paper concludes that PakLocCorpus can play a pivotal role in legitimizing Pakistani English and transforming English language pedagogy in Pakistan.